Rebhi, Wala and Ben Yahia, Nesrine and Bellamine Ben Saoud, Narjès and Hanachi, Chihab
Towards Contextualizing Community Detection in Dynamic Social Networks.
(2017)
In: 10th International and Interdisciplinary Conference on Modeling and Using Context (CONTEXT 2017), 20 June 2017 - 23 June 2017 (Paris, France).
|
(Document in English)
PDF (Author's version) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader 520kB |
Official URL: https://doi.org/10.1007/978-3-319-57837-8_26
Abstract
With the growing number of users and the huge amount of information in dynamic social networks, contextualizing community detection has been a challenging task. Thus, modeling these social networks is a key issue for the process of contextualized community detection. In this work, we propose a temporal multiplex information graph-based model to represent dynamic social networks: we consider simultaneously the social network dynamicity, its structure (different social connections) and various members’ profiles so as to calculate similarities between “nodes” in each specific context. Finally a comparative study on a real social network shows the efficiency of our approach and illustrates practical uses.
Repository Staff Only: item control page